The Limits of Artificial Intelligence

At a lecture hall in Manila, tech entrepreneur and investment icon Joseph Plazo drew a bold line on what technology can realistically offer for the world of investing—and why that distinction matters now more than ever.

You could feel the electricity in the crowd. Young scholars—some furiously taking notes, others capturing every word via livestream—waited for a man revered for blending code with contrarianism.

“Machines will execute trades flawlessly,” he said with gravity. “But understanding the why—that’s still on you.”

Over the next lecture, Plazo delivered a fast-paced masterclass, balancing data science with real-world decision making. His central claim: AI is brilliant, but blind.

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Top Students Meet a Tough Truth

Before him sat students and faculty from prestigious universities across Asia, assembled under a pan-Asian finance forum.

Many expected a victory lap of AI's dominance. Instead, they got a reality check.

“There’s a growing religion around AI,” said Prof. Maria Castillo, a respected AI ethicist from the UK. “We need this kind of discomfort in academia.”

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The Machine’s Blindness: Plazo’s Case for Caution

Plazo’s core thesis was both simple and unsettling: AI does not grasp nuance.

“AI won’t flinch, but neither will it foresee,” he warned. “It recognizes patterns—but ignores the power structures.”

He cited examples like the market chaos of early 2020, noting, “Machines were late to the signal. People weren’t.”

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Wisdom in a World of Code

Plazo didn’t argue against AI—but for boundaries.

“AI is the microscope—you get more info choose what to zoom in on,” he said. It analyzes—but lacks awareness.

Students pressed him on AI in news and social chatter, to which Plazo acknowledged: “Of course, it parses language patterns—but it can’t discern hesitation in a policymaker’s tone.”

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Asia Reflects: From Tech Worship to Tech Wisdom

The talk hit hard.

“I used to think AI just needed more data,” said Lee Min-Seo, a finance student from Seoul. “Now I realize it also needs wisdom—and that’s the hard part.”

In a post-talk panel, faculty and entrepreneurs echoed the caution. “These kids speak machine natively—but instinct,” said Dr. Raymond Tan, “is not insight.”

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What’s Next? AI That Thinks in Narratives

Plazo shared that his firm is building “co-intelligence”—AI that blends pattern recognition with real-world awareness.

“No machine can tell you who to trust,” he reminded. “Capital still requires conviction.”

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Standing Ovation, Unfinished Conversations

As Plazo exited the stage, the hall erupted. But more importantly, they started debating.

“I came for machine learning,” said a PhD candidate. “Instead, I got something more powerful—perspective.”

Perhaps, in drawing boundaries for AI, we expand our own.

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